Earnings Autocorrelation and the Post-Earnings-Announcement Drift: Experimental Evidence

Josef Fink, Stefan Palan () and Erik Theissen

Journal of Financial and Quantitative Analysis, 2024, vol. 59, issue 6, 2799-2837

Abstract: Post-earnings-announcement drift (PEAD) is one of the most solidly documented asset pricing anomalies. We use the controlled conditions of the experimental lab to investigate whether earnings autocorrelation is the driving cause of this anomaly. We observe PEAD in settings with uncorrelated and correlated earnings surprises, confirming that earnings autocorrelation is not a necessary condition for PEAD. Instead, it acts as an accelerator: PEAD is stronger when earnings surprises are correlated. We further show that market prices underadjust to fundamental value changes, and that trading strategies can profitably exploit the PEAD.

Date: 2024
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Working Paper: Earnings autocorrelation and the post-earnings-announcement drift: Experimental evidence (2020)
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